* Added support for other features for already supported models
* Partial support for causal and seq2seq models
* Partial support for causal and seq2seq models
* OnnxSeq2SeqConfigWithPast to support seq2seq models
* Parameterized the onnx tests
* Restored run_mlm.py
* Restored run_mlm.py
* [WIP] BART update
* BART and MBART
* Added comments
* Another sequence length of the past_key_values
* Add support for exporting PyTorch LayoutLM to ONNX
* Added tests for converting LayoutLM to ONNX
* Add support for exporting PyTorch LayoutLM to ONNX
* Added tests for converting LayoutLM to ONNX
* cleanup
* Removed regression/ folder
* Add support for exporting PyTorch LayoutLM to ONNX
* Added tests for converting LayoutLM to ONNX
* cleanup
* Fixed import error
* Remove unnecessary import statements
* Changed max_2d_positions from class variable to instance variable of the config class
* Add support for exporting PyTorch LayoutLM to ONNX
* Added tests for converting LayoutLM to ONNX
* cleanup
* Add support for exporting PyTorch LayoutLM to ONNX
* cleanup
* Fixed import error
* Changed max_2d_positions from class variable to instance variable of the config class
* Use super class generate_dummy_inputs method
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>
* Add support for Masked LM, sequence classification and token classification
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>
* Removed uncessary import and method
* Fixed code styling
* Raise error if PyTorch is not installed
* Remove unnecessary import statement
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>
T5 with past ONNX export, and more explicit past_key_values inputs and outputs names for ONNX model
Authored-by: Michael Benayoun <michael@huggingface.co>
* Raise an issue if the pytorch version is < 1.8.0
* Attempt to add a test to ensure it correctly raises.
* Missing docstring.
* Second attempt, patch with string absolute import.
* Let's do the call before checking it was called ...
* use the correct function ... 🤦
* Raise ImportError and AssertionError respectively when unable to find torch and torch version is not sufficient.
* Correct path mock patching
* relax constraint for torch_onnx_dict_inputs to ge instead of eq.
* Style.
* Split each version requirements for torch.
* Let's compare version directly.
* Import torch_version after checking pytorch is installed.
* @require_torch
* Laying down building stone for more flexible ONNX export capabilities
* Ability to provide a map of config key to override before exporting.
* Makes it possible to export BART with/without past keys.
* Supports simple mathematical syntax for OnnxVariable.repeated
* Effectively apply value override from onnx config for model
* Supports export with additional features such as with-past for seq2seq
* Store the output path directly in the args for uniform usage across.
* Make BART_ONNX_CONFIG_* constants and fix imports.
* Support BERT model.
* Use tokenizer for more flexibility in defining the inputs of a model.
* Add TODO as remainder to provide the batch/sequence_length as CLI args
* Enable optimizations to be done on the model.
* Enable GPT2 + past
* Improve model validation with outputs containing nested structures
* Enable Roberta
* Enable Albert
* Albert requires opset >= 12
* BERT-like models requires opset >= 12
* Remove double printing.
* Enable XLM-Roberta
* Enable DistilBERT
* Disable optimization by default
* Fix missing setattr when applying optimizer_features
* Add value field to OnnxVariable to define constant input (not from tokenizers)
* Add T5 support.
* Simplify model type retrieval
* Example exporting token_classification pipeline for DistilBERT.
* Refactoring to package `transformers.onnx`
* Solve circular dependency & __main__
* Remove unnecessary imports in `__init__`
* Licences
* Use @Narsil's suggestion to forward the model's configuration to the ONNXConfig to avoid interpolation.
* Onnx export v2 fixes (#12388)
* Tiny fixes
Remove `convert_pytorch` from onnxruntime-less runtimes
Correct reference to model
* Style
* Fix Copied from
* LongFormer ONNX config.
* Removed optimizations
* Remvoe bad merge relicas.
* Remove unused constants.
* Remove some deleted constants from imports.
* Fix unittest to remove usage of PyTorch model for onnx.utils.
* Fix distilbert export
* Enable ONNX export test for supported model.
* Style.
* Fix lint.
* Enable all supported default models.
* GPT2 only has one output
* Fix bad property name when overriding config.
* Added unittests and docstrings.
* Disable with_past tests for now.
* Enable outputs validation for default export.
* Remove graph opt lvls.
* Last commit with on-going past commented.
* Style.
* Disabled `with_past` for now
* Remove unused imports.
* Remove framework argument
* Remove TFPreTrainedModel reference
* Add documentation
* Add onnxruntime tests to CircleCI
* Add test
* Rename `convert_pytorch` to `export`
* Use OrderedDict for dummy inputs
* WIP Wav2Vec2
* Revert "WIP Wav2Vec2"
This reverts commit f665efb04c92525c3530e589029f0ae7afdf603e.
* Style
* Use OrderedDict for I/O
* Style.
* Specify OrderedDict documentation.
* Style :)
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
